ZENG Guoqiang, LIU Li, SHENG Lei, BAI Nan. Location Selection and Scheduling Optimization of Material Storage in Manufacturing Workshop[J]. International Journal of Plant Engineering and Management, 2019, 24(4): 206-218

Location Selection and Scheduling Optimization of Material Storage in Manufacturing Workshop
ZENG Guoqiang, LIU Li, SHENG Lei, BAI Nan
School of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610616, China
Based on improved immune algorithm, the location of material storage in manufacturing workshop is studied. Intelligent optimization algorithms include particle swarm optimization algorithm, genetic selection algorithm, simulated annealing algorithm, tabu search algorithm and so on. According to the non-linear constraints, the objective function is established to solve the minimum energy consumption of material distribution. The improved immune algorithm can solve the complex problem of manufacturing workshop, and the material storage location and scheduling scheme can be obtained by combining simulation software. Scheduling optimization involves material warehousing, sorting, loading and unloading, handling and so on. Using the one-to-one accurate distribution principle and MATLAB software to simulate and analyze, the location of material warehousing in manufacturing workshop is determined, and the material distribution and scheduling are studied.
Key words:    immune algorithm    manufacturing workshop    material storage location    MATLAB    scheduling optimization   
Received: 2019-08-25     Revised:
DOI: 10.13434/j.cnki.1007-4546.2019.0402
Corresponding author:     Email:
Author description:
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ZENG Guoqiang

[1] Dong D, Wang X N, He Y P. Design of railway computer interlocking search algorithm and implementation of interlocking software[J]. International Journal of Plant Engineering and Management, 2019,24(2):73-80(in Chinese)
[2] Cheng G, Yin J. Logistics technology and equipment[M]. Beijing:Mechinery Industry Press, 2018(in Chinese)
[3] Ma X G, Liang Y, Yang H H. Modern logistics system modeling, simulation and application[M]. Beijing:Mechanical Industry Press, 2017(in Chinese)
[4] Fu M, Li J H, Wu Y F, et al. Observer-based state feedback control to suppress stick-slip vibrations in oil well drill-string[J]. International Journal of Plant Engineering and Management, 2019,24(2):65-71(in Chinese)
[5] Zhuo K F, Deng Y M, Wu H W, et al. Influence of multi-component failure on mechanical product design change[J]. International Journal of Plant Engineering and Management, 2019,24(2):81-90(in Chinese)
[6] Huang Y, Li J Y, Yan X T. Study on dynamic scheduling of duel resource constrained job shop[M]. Mechanical Science and Technology for Aerospace Engineering, 2016,6(6):968-974(in Chinese)
[7] Tian X L, Duan F. Immune optimal algorithm, modeling and application[M]. Beijing:National Defence Industry Press, 2013(in Chinese)
[8] Yun Y H, Hwang E J, Kim Y H. Adaptive genetic algorithm for energy-efficient task scheduling on asymmetric multiprocessor system-on-chip[J]. Microprocessors and Microsystems, 2019,66:19-30
[9] Ferro G, Laureri F, Minciardi R, et al. A predictive discrete event approach for the optimal charging of electric vehicles in microgrids[J]. Control Engineering Practice,2019,86:11-23
[10] Wang C, Mu D. Modeling and optimization method of vehicle routing problem in distribution enterprises[M]. Beijing:Beijing jiaotong University Press, 2016(in Chinese)
[11] Wu B. Vehicle routing problem in logistics distribution and intelligent optimization algorithms[M]. Beijing:Economy &Management Publishing House, 2013(in Chinese)
[12] Yao J M. Theory and method of supply chain scheduling under mass customization[M]. Beijing:China Material Publishing House, 2009(in Chinese)
[13] Li D W, Wang L, Xiong Y. Logistics system location scheduling model and algorithm[M]. Beijing:Science Press, 2014(in Chinese)
[14] Dulebenets M A. A delay start parallel evolutionary algorithm for just-in-time truck scheduling at a cross-docking facility[J]. International Journal of Production Economics, 2019,212:236-258
[15] Prokhorchenko A, Parkhomenko L, Kyman A, et al. Impro-vement of the technology of accelerated passage of low-capacity car traffic on the besis of scheduling of grouped trains of operational purpose[J]. Procedia Computer Science, 2019,149:86-94
[16] Chen H H, Wang Z H, Zhang R F. et al. Distributed optimal dispatching model of wind power Grid-connected system with virtual power plant[J]. Journal of Electrical Engineering of China, 2019,39(9):2615-2624(in Chinese)
[17] Xiong H, Fan H, Jiang G, et al. A simulation-based study of dispatching rules in a dynamic job shop scheduling problem with batch release and extended technical precedence constraints[J]. European Journal of Operational Research, 2017,257:13-24
[18] Mo H W, Zuo X Q. Artificial immune system[M]. Beijing:Science Press, 2009(in Chinese)
[19] Yang J M, Zhang H, Feng X J. An explicit iteration algorithm for structural reliability and its realization by MATLAB[J]. International Journal of Plant Engineering and Management, 2008,13(4):220-224(in Chinese)
[20] Hu C J. Zhang J. An immune differential evolution algorithm using clonal selection[J]. Computer Applied Research, 2013,30(6):46-48,57(in Chinese)